4.6 Article

High-Accuracy Elevation Data at Large Scales from Airborne Single-Pass SAR Interferometry

期刊

FRONTIERS IN EARTH SCIENCE
卷 3, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/feart.2015.00088

关键词

DEM; SAR; single-pass interferometry; LiDAR; floodplain topography; inundation

资金

  1. National Aeronautics and Space Administration (NASA) [NNX13AD99G]
  2. Google Inc.

向作者/读者索取更多资源

Digital elevation models (DEMs) are essential data sets for disaster risk management and humanitarian relief services as well as many environmental process models. At present, on the one hand, globally available DEMs only meet the basic requirements and for many services and modeling studies are not of high enough spatial resolution and lack accuracy in the vertical. On the other hand, LiDAR-DEMs are of very high spatial resolution and great vertical accuracy but acquisition operations can be very costly for spatial scales larger than a couple of hundred km2 and also have severe limitations in wetland areas and under cloudy and rainy conditions. The ideal situation would thus be to have a DEM technology that allows larger spatial coverage than LiDAR but without compromising resolution and vertical accuracy and still performing under some adverse weather conditions and at a reasonable cost. In this paper, we present a novel single pass In-SAR technology for airborne vehicles that is cost-effective and can generate DEMs with a vertical error of around 0.3 m for an average spatial resolution of 3 m. To demonstrate this capability, we compare a sample single-pass In-SAR Ka-band DEM of the California Central Valley from the NASA/JPL airborne GLISTIN-A to a high-resolution LiDAR DEM. We also perform a simple sensitivity analysis to floodplain inundation. Based on the findings of our analysis, we argue that this type of technology can and should be used to replace large regions of globally available lower resolution DEMs, particularly in coastal, delta and floodplain areas where a high number of assets, habitats and lives are at risk from natural disasters. We conclude with a discussion on requirements, advantages and caveats in terms of instrument and data processing.

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